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Strong Data Science Scholarship at University of Toronto in Canada, 2017

The University of Toronto is inviting applications for Strong Data Science Scholarship to study in Canada. The Scholarship is available to pursue secondary and post-secondary students.

The aim of Scholarship is to provide financial help to the students interested in pursuing a career in data science.

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The University of Toronto (U of T, UToronto, or Toronto) is a public research university in Toronto, Ontario, Canada on the grounds that surround Queen’s Park.

Course Level: The Scholarship is available to pursue secondary and post-secondary students.

Study Subject: The Scholarship will be awarded in the field of data science.

Scholarship Award: The Scholarship will be awarded $1,000 (USD).

Number of Scholarships: Not Known

Scholarship can be taken in the Canada

Eligibility: The following criteria must be met in order for applicants to be eligible for scholarship:

  • The project must use publicly-available, open-access data.
  • All analyses, visualizations, and reports must be original.
  • Students can work individually or as teams.
  • Each student or team may only make a single submission.
  • All submissions must include the source code and data necessary to reproduce the analysis.
  • Submissions must be hosted at a public repository, such as GitHub.
  • All applicants must be currently registered as students at a college/university in the United States or Canada.

 Nationality: The United States or Canada applicants can apply for the Scholarship.

College Admission Requirement

Entrance Requirements: Applicants must have their previous degree.

English language Requirements: Applicants need to demonstrate that they have a good level of written and spoken English the candidate should have a very good command over English language.

Canada Scholarship

How to Apply: Application procedure:

  • Find a publicly-available dataset.
  • Choose an interesting research question in the public interest that can be addressed using these data.
  • Using the programming language(s) of your choice (e.g., R, Python), analyze, visualize, and interpret the data.
  • Code your analysis such that we can re-run it ourselves to reproduce your results and visualizations.
  • Create a presentation (up to 20 slides) that clearly outlines your research question, methods, and findings.
  • Submit your presentation as a PDF and a link to your project’s reproducible source code repository to [email protected] by the deadline above.

Application Deadline: The Application Deadline is June 1, 2017.

Scholarship Link